Data Scoping: Job Search Effort/Behaviour
Ebba Mark
2025-03-06
Overview
The following document summarises current progress on identifying a data source to inform the job search behaviour in the ABM. The following looks into the three determinants of job-finding that we have thus far identified as being relevant (plausibly independent and potentially most relevant):
- Dynamic selection (heterogeneity of job seekers - fitness & skills match for the current labour market)
- Duration dependence (job-finding probability decreases over time spent unemployed indendent of job-seeker characteristics)
- Search effort (individuals can exert greater search effort to counteract duration dependence - generally exhibits a countercyclical behaviour - job search effort increases as the economy recedes)
Current idea: If we view dynamic selection simply as worker heterogeneity, duration dependence as an endogenous process of skill deterioration or signal to employers (up to a certain point), and search effort as responsive to labour market conditions, we will have quasi-independent elements in the job-finding probability of workers in the model!
Goals:
Identify parameters relevant to agent search behaviour in the ABM.
Assess data quality for deriving empirical estimates of these parameters.
Analysis so far:
I first focus on replicating and extending the empirical analysis that speaks to the three determinants above (dynamic selection, duration dependence, search effort)
- (Replicated with additional data for unemployed jobseekers) Mukoyama et al. 2018: Job Search Over the Business Cycle
They provide a novel measure of job search effort exploiting the American Time Use and Current Population Surveys which can be reduced to just the intensive margin (changes in search effort by worker!). At the moment, I think this will be the most useful input for our model.
Abstract: We examine the cyclicality of search effort using time-series, cross-state, and individual variation and find that it is countercyclical. We then set up a search and matching model with endogenous search effort and show that search effort does not amplify labor market fluctuations but rather dampens them. Lastly, we examine the role of search effort in driving recent unemployment dynamics and show that the unemployment rate would have been 0.5 to 1 percentage points higher in the 2008–2014 period had search effort not increased.
(Replicate with additional data from 2017-2024) Eeckhout et al. 2019 Unemployment Cycles
(Replicated with additional data from 2019-2024) Mueller et al. 2021: Job Seekers’ Perceptions and Employment Prospects: Heterogeneity, Duration Dependence and Bias
The authors claim to disentangle the effects of duration dependence and dynamic selection by using job seekers’ elicited beliefs about job-finding. Assuming (and confirming empirically) that job-seekers have realistic initial beliefs about job-finding they isolate the heterogeneity in jobseekers from true duration dependence. Ultimately, they find that dynamic selection selection explains most of the negative duration dependence (rather than pure, true duration dependence).
Findings: Results are remarkably consistent even when including additional data from 2019-2024.
- Survey of Consumer Expectations Reservation Wages, Accepted Wages, and Wage Expectations The data is unfortunately sparse and linking outcomes to reservation wages is difficult. However, in a cross-sectional setting we are able to deduce some weak relationships between Unemployment Duration and Absolute Reservation Wages and Wage Expectations.
Analyses
Mueller et al. Job Seekers’ Perceptions and Employment Prospects: Heterogeneity, Duration Dependence and Bias
Mueller et al: Job Seekers’ Perceptions and Employment Prospects
##
## Descriptive Statistics (SCE)
## ===============================================================
## Variable Orig. 2013-19 2013-24 2020-24
## ---------------------------------------------------------------
## High-School Degree or Less 44.5 40.6 36.9
## Some College Education 32.4 34.9 37.6
## College Degree or More 23.1 24.6 25.6
## Age 20-34 25.4 27.2 30.0
## Age 35-49 33.5 33.6 35.3
## Age 50-65 41.1 39.2 34.8
## Female 59.3 61.2 60.8
## Black 19.1 17.9 16.4
## Hispanic 12.5 13.0 12.6
## UE transition rate 18.7 19.1 18.2
## UE transition rate: ST 25.8 26.5 24.3
## UE transition rate: LT 12.7 12.7 12.3
## # respondents 948 1,367 433
## # respondents w/ at least 2 u obs 534 780 252
## # observations 2,597 3,926 1,347
## ---------------------------------------------------------------
## [1] "Table 2—Regressions of Realized on Elicited 3-Month Job-Finding Probabilities (SCE)"
## [1] "Panel A. Contemporaneous elicitations"
##
## ========================================================================
## Dependent variable:
## ----------------------------------------------------
## T+3 UE Transitions (3-Months)
## Orig. 2013-19 2013-24 2020-24
## (1) (2) (3)
## ------------------------------------------------------------------------
## find_job_3mon 0.464*** 0.396*** 0.265***
## (0.045) (0.036) (0.067)
##
## 1 | userid
##
##
## Constant -0.104 -0.080 -0.136
## (0.169) (0.137) (0.267)
##
## ------------------------------------------------------------------------
## Observations 1,201 1,911 673
## R2 0.218 0.139 0.105
## Adjusted R2 0.207 0.132 0.083
## Residual Std. Error 0.467 (df = 1184) 0.475 (df = 1894) 0.478 (df = 656)
## ========================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
##
## ==========================================================================
## Dependent variable:
## ----------------------------------------------------
## T+3 UE Transitions (3-Months)
## Orig. 2013-19 2013-24 2020-24
## (1) (2) (3)
## --------------------------------------------------------------------------
## find_job_3mon 0.501*** 0.418*** 0.391***
## (0.061) (0.051) (0.094)
##
## findjob_3mon_longterm -0.258*** -0.170** -0.360***
## (0.088) (0.071) (0.133)
##
## longterm_unemployed -0.078 -0.127*** -0.043
## (0.051) (0.041) (0.075)
##
## 1 | userid
##
##
## Constant -0.062 -0.063 -0.402
## (0.175) (0.139) (0.266)
##
## --------------------------------------------------------------------------
## Observations 1,201 1,911 673
## R2 0.259 0.182 0.155
## Adjusted R2 0.248 0.174 0.132
## Residual Std. Error 0.455 (df = 1182) 0.464 (df = 1892) 0.465 (df = 654)
## ==========================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
## [1] "Panel B. Lagged elicitations"
##
## ======================================================================
## Dependent variable:
## --------------------------------------------------
## T+3 UE Transitions (3-Months)
## Orig. 2013-19 2013-24 2020-24
## (1) (2) (3)
## ----------------------------------------------------------------------
## tplus3_percep_3mon 0.332*** 0.241*** 0.203**
## (0.067) (0.056) (0.102)
##
## 1 | userid
##
##
## Constant 0.304 0.490** 0.451
## (0.270) (0.207) (0.394)
##
## ----------------------------------------------------------------------
## Observations 474 798 300
## R2 0.168 0.090 0.179
## Adjusted R2 0.139 0.071 0.132
## Residual Std. Error 0.398 (df = 457) 0.436 (df = 781) 0.447 (df = 283)
## ======================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
##
## ======================================================================
## Dependent variable:
## --------------------------------------------------
## T+3 UE Transitions (3-Months)
## Orig. 2013-19 2013-24 2020-24
## (1) (2) (3)
## ----------------------------------------------------------------------
## find_job_3mon 0.301*** 0.205*** -0.035
## (0.069) (0.058) (0.110)
##
## 1 | userid
##
##
## Constant 0.201 0.422** 0.361
## (0.274) (0.207) (0.400)
##
## ----------------------------------------------------------------------
## Observations 474 798 300
## R2 0.159 0.083 0.168
## Adjusted R2 0.129 0.064 0.121
## Residual Std. Error 0.400 (df = 457) 0.437 (df = 781) 0.450 (df = 283)
## ======================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01
## [1] "Table 4—Linear Regressions of Elicited Job-Finding Probabilities on Duration of Unemployment"
##
##
## Table: Table 4 - Panel A: Linear Regressions of Elicited Job-Finding Probabilities on Duration of Unemployment (SCE)
##
## | | (1) | (2) | (3) | (4) |
## |:-------------------------------|---------:|---------:|---------:|---------:|
## | Unemployment Duration (Months) | -0.0057 | -0.0050 | -0.0043 | 0.0022 |
## | | (0.0007) | (0.0007) | (0.0006) | (0.0049) |
## | Num.Obs. | 882 | 2281 | 2281 | 2281 |
## | R2 | 0.110 | 0.090 | 0.155 | 0.824 |
## | Unemployment Duration (Months) | -0.0050 | -0.0048 | -0.0042 | -0.0026 |
## | | (0.0006) | (0.0006) | (0.0005) | (0.0034) |
## | Num.Obs. | 1265 | 3423 | 3399 | 3423 |
## | R2 | 0.067 | 0.065 | 0.109 | 0.817 |
## | Unemployment Duration (Months) | -0.0011 | -0.0035 | -0.0039 | -0.0077 |
## | | (0.0013) | (0.0012) | (0.0013) | (0.0036) |
## | Num.Obs. | 395 | 1150 | 1140 | 1150 |
## | R2 | 0.002 | 0.019 | 0.118 | 0.838 |
##
## __Note:__
## ^^ Standard errors are clustered at the user or spell level as indicated.
Reservation Wages
Exploring the effect of unemployment duration on reservation wages, accepted wages, and expected wage offers.
Survey of Consumer Expectations Reservation Wages, Accepted Wages, and Wage Expectations (2014-2022) The data is unfortunately sparse and linking outcomes to reservation wages is difficult. However, in a cross-sectional setting we are able to deduce some weak relationships between Unemployment Duration and Absolute Reservation Wages and Wage Expectations.
## [1] "Plots of RESERVATION WAGE versus latest, current wage"
## [1] "Plots of EXPECTED OFFER versus latest, current, reservation wage"
## [1] "Plots of ACCEPTED SALARY versus latest, current, reservation wage"
##
##
## Table: Reservation Wages and Unemployment Duration
##
## | | ResWage | ResWage w.c | ResWage/LastWage | ResWage/LastWage w.c |
## |:------------|----------:|------------:|-----------------:|---------------------:|
## | (Intercept) | 10.579*** | 10.276*** | 1.002*** | 1.030*** |
## | | (0.045) | (0.101) | (0.026) | (0.072) |
## | udur_bins | -0.055*** | -0.028* | -0.013 | -0.015 |
## | | (0.016) | (0.013) | (0.009) | (0.009) |
## |:------------|----------:|------------:|-----------------:|---------------------:|
## | Num.Obs. | 708 | 704 | 700 | 696 |
## | R2 | 0.016 | 0.436 | 0.003 | 0.106 |
## | R2 Adj. | 0.015 | 0.423 | 0.001 | 0.086 |
## | AIC | 16082.3 | 15627.4 | 492.1 | 441.7 |
## | BIC | 16096.0 | 15704.8 | 505.7 | 519.0 |
## | Log.Lik. | -646.262 | -446.774 | -243.030 | -203.852 |
## | RMSE | 0.57 | 0.45 | 0.32 | 0.31 |
##
## __Note:__
## ^^ + p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
##
##
## Table: Accepted Wages and Unemployment Duration
##
## | | AccptWage | AccptWage w.c | AccptWage/ResWage | AccptWage/ResWage w.c |
## |:------------|----------:|--------------:|------------------:|----------------------:|
## | (Intercept) | 10.890*** | 10.734*** | 0.930*** | 0.637* |
## | | (0.152) | (0.611) | (0.054) | (0.308) |
## | udur_bins | -0.083 | -0.042 | -0.002 | -0.008 |
## | | (0.060) | (0.050) | (0.021) | (0.024) |
## |:------------|----------:|--------------:|------------------:|----------------------:|
## | Num.Obs. | 59 | 58 | 63 | 62 |
## | R2 | 0.033 | 0.644 | 0.000 | 0.267 |
## | R2 Adj. | 0.016 | 0.528 | -0.016 | 0.049 |
## | AIC | 1373.7 | 1318.5 | -8.6 | -1.1 |
## | BIC | 1379.9 | 1351.4 | -2.2 | 33.0 |
## | Log.Lik. | -52.246 | -22.561 | 7.292 | 16.530 |
## | RMSE | 0.55 | 0.37 | 0.20 | 0.19 |
##
## __Note:__
## ^^ + p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001
##
##
## Table: Expected Wages and Unemployment Duration
##
## | | ExpWage/ResWage | ExpWage/ResWage w.c | ExpWage/LastWage | ExpWage/LastWage w.c |
## |:------------|----------------:|--------------------:|-----------------:|---------------------:|
## | (Intercept) | 1.124*** | 1.494*** | 1.137*** | 1.341*** |
## | | (0.029) | (0.091) | (0.034) | (0.104) |
## | udur_bins | -0.015 | -0.006 | -0.040** | -0.034** |
## | | (0.011) | (0.011) | (0.012) | (0.013) |
## |:------------|----------------:|--------------------:|-----------------:|---------------------:|
## | Num.Obs. | 534 | 530 | 529 | 525 |
## | R2 | 0.004 | 0.100 | 0.019 | 0.138 |
## | R2 Adj. | 0.002 | 0.073 | 0.018 | 0.112 |
## | AIC | 387.4 | 360.3 | 532.3 | 488.6 |
## | BIC | 400.3 | 432.9 | 545.2 | 561.1 |
## | Log.Lik. | -190.716 | -163.132 | -263.169 | -227.312 |
## | RMSE | 0.32 | 0.32 | 0.35 | 0.34 |
##
## __Note:__
## ^^ + p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001Draft Plots: Behavioural Parameters Relevant to Working Paper
